Triple

T15011672
Position Surface form Disambiguated ID Type / Status
Subject Sind Province E377852 entity
Predicate contains P35 FINISHED
Object Hyderabad E119141 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Hyderabad | Statement: [Sind Province, contains, Hyderabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hyderabad
Context triple: [Sind Province, contains, Hyderabad]
  • A. Hyderabad
    Hyderabad is a major city in southern India known for its historic Charminar monument, rich Hyderabadi cuisine, and growing technology industry.
  • B. Hyderabad chosen
    Hyderabad is a major city in the Sindh province of Pakistan, known for its historical significance, vibrant culture, and role as an important commercial and industrial center.
  • C. Secunderabad
    Secunderabad is a major twin city of Hyderabad in the Indian state of Telangana, known as an important commercial and transportation hub with a significant military presence.
  • D. Vijayawada
    Vijayawada is a major commercial and cultural city in the Indian state of Andhra Pradesh, known as a key transportation hub and an important center for trade, education, and politics in the region.
  • E. Hyderabad Metropolitan Region
    The Hyderabad Metropolitan Region is a large urban agglomeration in and around Hyderabad, India, encompassing major residential, commercial, and technology hubs under a unified metropolitan planning and governance framework.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d85cd3a3c881908c71fc424d459c17 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7613cec8190ac25e3f68c5d0edf completed April 15, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe967e9c208190a00a82122b8c884c completed May 9, 2026, 2:05 a.m.
Created at: April 10, 2026, 2:55 a.m.